{"id":"https://openalex.org/W4409196824","doi":"https://doi.org/10.30574/wjarr.2023.20.1.2144","title":"Machine learning implementation in Python: Performance analysis of different libraries","display_name":"Machine learning implementation in Python: Performance analysis of different libraries","publication_year":2023,"publication_date":"2023-10-30","ids":{"openalex":"https://openalex.org/W4409196824","doi":"https://doi.org/10.30574/wjarr.2023.20.1.2144"},"language":"en","primary_location":{"id":"doi:10.30574/wjarr.2023.20.1.2144","doi":"https://doi.org/10.30574/wjarr.2023.20.1.2144","is_oa":true,"landing_page_url":"https://doi.org/10.30574/wjarr.2023.20.1.2144","pdf_url":"https://wjarr.com/sites/default/files/WJARR-2023-2144.pdf","source":{"id":"https://openalex.org/S4210223820","display_name":"World Journal of Advanced Research and Reviews","issn_l":"2581-9615","issn":["2581-9615"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/P4383735917","host_organization_name":"GSC Online Press","host_organization_lineage":["https://openalex.org/P4383735917"],"host_organization_lineage_names":["GSC Online Press"],"type":"journal"},"license":"cc-by-nc-sa","license_id":"https://openalex.org/licenses/cc-by-nc-sa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"World Journal of Advanced Research and Reviews","raw_type":"journal-article"},"volume":null,"type":"article","is_traditional":true,"indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://wjarr.com/sites/default/files/WJARR-2023-2144.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Praggnya Kanungo","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I51556381","display_name":"University of Virginia","ror":"https://ror.org/0153tk833","country_code":"US","type":"education","lineage":["https://openalex.org/I51556381"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Praggnya Kanungo","raw_affiliation_strings":["Student, Computer Science , University of Virginia , USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Student, Computer Science , University of Virginia , USA","institution_ids":["https://openalex.org/I51556381"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I51556381"],"apc_list":null,"apc_paid":null,"fwci":0.1402,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":{"value":0.39157236,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":88,"max":95},"biblio":{"volume":"20","issue":"1","first_page":"1390","last_page":"1398"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12535","display_name":"Machine Learning and Data Classification","score":0.5088000297546387,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12535","display_name":"Machine Learning and Data Classification","score":0.5088000297546387,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T13650","display_name":"Computational Physics and Python Applications","score":0.27079999446868896,"subfield":{"id":"https://openalex.org/subfields/1712","display_name":"Software"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T13373","display_name":"Data Mining and Machine Learning Applications","score":0.06719999760389328,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/machine-learning-library","display_name":"machine learning library","score":0.8740000128746033},{"id":"https://openalex.org/keywords/python","display_name":"Python","score":0.7870000004768372},{"id":"https://openalex.org/keywords/scikit-learn","display_name":"scikit-learn","score":0.8130000233650208},{"id":"https://openalex.org/keywords/tensorflow","display_name":"TensorFlow","score":1.0},{"id":"https://openalex.org/keywords/pytorch","display_name":"PyTorch","score":1.0},{"id":"https://openalex.org/keywords/xgboost","display_name":"XGBoost","score":1.0},{"id":"https://openalex.org/keywords/execution-time","display_name":"execution time","score":0.8899999856948853},{"id":"https://openalex.org/keywords/memory-usage","display_name":"memory usage","score":1.0},{"id":"https://openalex.org/keywords/deep-learning","display_name":"deep learning","score":0.8489999771118164},{"id":"https://openalex.org/keywords/gradient-boosting","display_name":"gradient boosting","score":0.9629999995231628},{"id":"https://openalex.org/keywords/classification","display_name":"classification","score":0.8700000047683716},{"id":"https://openalex.org/keywords/regression-analysis","display_name":"regression analysis","score":0.9959999918937683},{"id":"https://openalex.org/keywords/clustering","display_name":"clustering","score":1.0}],"concepts":[{"id":"https://openalex.org/C519991488","wikidata":"https://www.wikidata.org/wiki/Q28865","display_name":"Python (programming language)","level":2,"score":0.8901530504226685},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.697813868522644},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.38120877742767334},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3220246136188507},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.3088192939758301}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.30574/wjarr.2023.20.1.2144","doi":"https://doi.org/10.30574/wjarr.2023.20.1.2144","is_oa":true,"landing_page_url":"https://doi.org/10.30574/wjarr.2023.20.1.2144","pdf_url":"https://wjarr.com/sites/default/files/WJARR-2023-2144.pdf","source":{"id":"https://openalex.org/S4210223820","display_name":"World Journal of Advanced Research and Reviews","issn_l":"2581-9615","issn":["2581-9615"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/P4383735917","host_organization_name":"GSC Online Press","host_organization_lineage":["https://openalex.org/P4383735917"],"host_organization_lineage_names":["GSC Online Press"],"type":"journal"},"license":"cc-by-nc-sa","license_id":"https://openalex.org/licenses/cc-by-nc-sa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"World Journal of Advanced Research and Reviews","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.30574/wjarr.2023.20.1.2144","doi":"https://doi.org/10.30574/wjarr.2023.20.1.2144","is_oa":true,"landing_page_url":"https://doi.org/10.30574/wjarr.2023.20.1.2144","pdf_url":"https://wjarr.com/sites/default/files/WJARR-2023-2144.pdf","source":{"id":"https://openalex.org/S4210223820","display_name":"World Journal of Advanced Research and Reviews","issn_l":"2581-9615","issn":["2581-9615"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/P4383735917","host_organization_name":"GSC Online Press","host_organization_lineage":["https://openalex.org/P4383735917"],"host_organization_lineage_names":["GSC Online Press"],"type":"journal"},"license":"cc-by-nc-sa","license_id":"https://openalex.org/licenses/cc-by-nc-sa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"World Journal of Advanced Research and Reviews","raw_type":"journal-article"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4409196824.pdf","grobid_xml":"https://content.openalex.org/works/W4409196824.grobid-xml"},"referenced_works_count":9,"referenced_works":["https://openalex.org/W1503398984","https://openalex.org/W1554944419","https://openalex.org/W4401648389","https://openalex.org/W4401672023","https://openalex.org/W4401851369","https://openalex.org/W6629510986","https://openalex.org/W6922384728","https://openalex.org/W6991957103","https://openalex.org/W7014191107"],"related_works":["https://openalex.org/W4407140698","https://openalex.org/W7008516935","https://openalex.org/W3204565323","https://openalex.org/W3007310793","https://openalex.org/W4307648823","https://openalex.org/W4404756276","https://openalex.org/W4405294680","https://openalex.org/W7166712652","https://openalex.org/W4406237488","https://openalex.org/W2895731965"],"abstract_inverted_index":{"This":[0,117],"research":[1],"paper":[2],"presents":[3],"a":[4],"comprehensive":[5],"performance":[6,104],"analysis":[7,118],"of":[8,22,92],"popular":[9],"machine":[10,30,78,96,129],"learning":[11,31,79,97,107,130],"libraries":[12,42,131],"in":[13,69,88,113,123],"Python.":[14],"We":[15],"compare":[16],"the":[17,71],"efficiency,":[18],"accuracy,":[19],"and":[20,26,36,46,56,67,90,100],"scalability":[21],"scikit-learn,":[23],"TensorFlow,":[24],"PyTorch,":[25],"XGBoost":[27,109],"across":[28],"various":[29],"tasks,":[32,98],"including":[33],"classification,":[34],"regression,":[35],"clustering.":[37],"The":[38,81],"study":[39],"evaluates":[40],"these":[41],"using":[43],"standardized":[44],"datasets":[45],"benchmarks,":[47],"considering":[48],"factors":[49],"such":[50],"as":[51],"execution":[52],"time,":[53],"memory":[54],"usage,":[55],"model":[57],"performance.":[58],"Our":[59],"findings":[60],"provide":[61],"valuable":[62],"insights":[63],"for":[64,75,94,105,132],"data":[65],"scientists":[66],"developers":[68],"selecting":[70],"most":[72],"appropriate":[73],"library":[74],"their":[76,133],"specific":[77],"projects.":[80,135],"results":[82],"demonstrate":[83],"that":[84],"while":[85],"scikit-learn":[86],"excels":[87],"simplicity":[89],"ease":[91],"use":[93],"traditional":[95],"TensorFlow":[99],"PyTorch":[101],"offer":[102],"superior":[103],"deep":[106],"applications.":[108],"shows":[110],"remarkable":[111],"efficiency":[112],"gradient":[114],"boosting":[115],"tasks.":[116],"aims":[119],"to":[120],"guide":[121],"practitioners":[122],"making":[124],"informed":[125],"decisions":[126],"when":[127],"choosing":[128],"Python-based":[134]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2024,"cited_by_count":1}],"updated_date":"2026-11-04T10:54:05.112534","created_date":"2025-04-06T00:00:00"}
